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Visual Studio Code was first announced on April 29, 2015 by Microsoft at the 2015 Build conference. A preview build was released shortly thereafter. [13]On November 18, 2015, the project "Visual Studio Code — Open Source" (also known as "Code — OSS"), on which Visual Studio Code is based, was released under the open-source MIT License and made available on GitHub.
GitHub Copilot is a code completion and automatic programming tool developed by GitHub and OpenAI that assists users of Visual Studio Code, Visual Studio, Neovim, and JetBrains integrated development environments (IDEs) by autocompleting code. [1]
Pylint is a static code analysis tool for the Python programming language. It is named following a common convention in Python of a "py" prefix, and a nod to the C programming lint program. It follows the style recommended by PEP 8, the Python style guide. [4] It is similar to Pychecker and Pyflakes, but includes the following features:
IPython continues to exist as a Python shell and a kernel for Jupyter, while the notebook and other language-agnostic parts of IPython moved under the Jupyter name. [ 4 ] [ 5 ] Jupyter supports execution environments (called "kernels") in several dozen languages, including Julia, R, Haskell , Ruby , and Python (via the IPython kernel).
Line length rule can be configured with option --linelength and file extensions can be configured with --extensions (by default: 'h', 'cpp', 'cc', 'cu' and 'cuh'). Some options can be stored in a configuration file CPPLINT.cfg. cpplint is implemented as a Python script. [3] It is distributed under the 3 clause BSD license.
Dracula is a color scheme for a large collection of desktop apps and website, with a focus on code editors and terminal emulators, created by Zeno Rocha.The scheme is exclusively available in dark mode.
Handlebars.js [7] is self-described as: . Handlebars.js is an extension to the Mustache templating language created by Chris Wanstrath. Handlebars.js and Mustache are both logicless templating languages that keep the view and the code separated like we all know they should be.
DVC is a free and open-source, platform-agnostic version system for data, machine learning models, and experiments. [1] It is designed to make ML models shareable, experiments reproducible, [2] and to track versions of models, data, and pipelines.